Marketing Analytics Engineer

About the role

N26 is a digital bank headquartered in Berlin, and the Marketing Analytics Engineer will play a central role in turning marketing data into actionable insights that drive business growth. This position sits at the intersection of data engineering and marketing strategy, supporting the growth and optimization of N26's customer acquisition and retention efforts across European markets. The engineer will work closely with the marketing team to design data pipelines, build dashboards, and develop models that measure campaign performance across multiple digital channels. The role requires a blend of technical proficiency and business acumen to translate complex data into clear recommendations for stakeholders and contribute directly to the company's marketing objectives.

Key facts

What you'll do

Design and maintain data pipelines that consolidate marketing data from multiple sources into a unified analytics environment.

Build and optimize dashboards and reporting tools that provide real-time visibility into campaign performance and customer acquisition metrics.

Develop statistical models and attribution frameworks to measure the effectiveness of marketing campaigns across digital channels.

Collaborate with the marketing team to define key performance indicators and establish measurement frameworks for new initiatives.

Write and maintain SQL queries to extract, transform, and analyze large datasets related to marketing activities.

Conduct A/B testing and experiment analysis to evaluate the impact of marketing strategies on user behavior and conversion.

Create automated reporting workflows that reduce manual effort and ensure stakeholders receive timely, accurate insights.

Partner with data engineering teams to improve data quality and ensure consistency across marketing data sources.

Present findings and recommendations to marketing leadership and cross-functional partners in clear, actionable formats.

Support the planning and forecasting process by providing data-driven insights on marketing budget allocation and ROI.

Monitor and report on marketing funnel metrics including click-through rates, cost per acquisition, and customer lifetime value to inform strategy adjustments.

Document analytical methodologies and data definitions to ensure reproducibility and enable team members to independently leverage marketing data assets.

Requirements

Bachelor's degree in a quantitative field such as statistics, mathematics, computer science, or a related discipline.

Experience with SQL and relational databases, including writing complex queries and optimizing database performance.

Proficiency in at least one programming language commonly used for data analysis, such as Python or R.

Familiarity with data visualization tools and the ability to build interactive dashboards for stakeholder consumption.

Understanding of marketing analytics concepts including attribution, cohort analysis, and campaign measurement.

Experience working with large datasets and demonstrating the ability to derive insights from complex data.

Strong analytical thinking with the ability to frame business questions in measurable, data-driven terms.

Excellent communication skills and the ability to present technical findings to non-technical audiences.

Comfortable working in a fast-paced environment with shifting priorities and the ability to manage multiple projects simultaneously.

Experience with data warehousing concepts and ETL processes is beneficial for understanding the broader data ecosystem.

Nice to have

Experience with marketing platforms and tools such as Google Analytics, Mixpanel, or similar customer analytics platforms.

Knowledge of A/B testing methodologies and experimentation frameworks used in product and marketing contexts.

Familiarity with cloud data platforms such as BigQuery, Snowflake, or Redshift for large-scale data processing.

Background in a fintech or banking environment, with an understanding of the unique data and regulatory considerations in financial services.

Experience with marketing attribution models including first-touch, last-touch, and multi-touch attribution to understand customer journey impact.

Skills & tools

SQL for data extraction, transformation, and analysis across large marketing datasets.

Python or R for statistical modeling, data manipulation, and automation of analytical workflows.

Data visualization platforms such as Tableau, Looker, or similar tools for building stakeholder-facing dashboards.

Google Analytics or equivalent web analytics platforms for tracking and analyzing digital marketing performance.

Spreadsheet tools such as Excel or Google Sheets for ad hoc analysis and rapid prototyping of ideas.

Version control systems such as Git for managing and tracking changes in analytical code and scripts.

Practical notes

This is a full-time position based in N26's Berlin office, with a hybrid work model that allows for a mix of in-office and remote days.

The hiring process includes multiple rounds of interviews, including a technical assessment focused on SQL and data analysis skills.

N26 offers competitive benefits including health insurance, retirement planning, and professional development budgets for continuing education.

Candidates should be prepared to demonstrate their analytical approach through a take-home exercise or live case study during the interview process.